Displaying all 18 publications

Abstract:
Sort:
  1. Complete fatty acid analysis data of flaxseed oil using GC-FID method
    Danish M, Nizami M
    Data Brief, 2019 Apr;23:103845.
    PMID: 31372470 DOI: 10.1016/j.dib.2019.103845
    The data presented in this article were generated through the gas chromatography (GC) with a flame ionization detector (FID). The flaxseed oil was converted into fatty acid methyl ester (FAME) then used in the GC with FID and observe the retention time of different fatty acid present in the flaxseed oil. The observed retention time was compared with the standard fatty acid to confirm the specific fatty acid presence in the flaxseed oil. The part of the data is used in the article "Optimization of the process variable for biodiesel production by transesterification of flaxseed oil and produced biodiesel characterizations" Renewable Energy journal (Ahmad et al., 2019).
  2. Prospects of banana waste utilization in wastewater treatment: A review
    Ahmad T, Danish M
    J Environ Manage, 2018 Jan 15;206:330-348.
    PMID: 29100146 DOI: 10.1016/j.jenvman.2017.10.061
    This review article explores utilization of banana waste (fruit peels, pseudo-stem, trunks, and leaves) as precursor materials to produce an adsorbent, and its application against environmental pollutants such as heavy metals, dyes, organic pollutants, pesticides, and various other gaseous pollutants. In recent past, quite a good number of research articles have been published on the utilization of low-cost adsorbents derived from biomass wastes. The literature survey on banana waste derived adsorbents shown that due to the abundance of banana waste worldwide, it also considered as low-cost adsorbents with promising future application against various environmental pollutants. Furthermore, raw banana biomass can be chemically modified to prepare efficient adsorbent as per requirement; chemical surface functional group modification may enhance the multiple uses of the adsorbent with industrial standard. It was evident from a literature survey that banana waste derived adsorbents have significant removal efficiency against various pollutants. Most of the published articles on banana waste derived adsorbents have been discussed critically, and the conclusion is drawn based on the results reported. Some results with poorly performed experiments were also discussed and pointed out their lacking in reporting. Based on literature survey, the future research prospect on banana wastes has a significant impact on upcoming research strategy.
  3. Effective Connectivity for Default Mode Network Analysis of Alcoholism
    Khan DM, Kamel N, Muzaimi M, Hill T
    Brain Connect, 2021 02;11(1):12-29.
    PMID: 32842756 DOI: 10.1089/brain.2019.0721
    Introduction: With the recent technical advances in brain imaging modalities such as magnetic resonance imaging, positron emission tomography, and functional magnetic resonance imaging (fMRI), researchers' interests have inclined over the years to study brain functions through the analysis of the variations in the statistical dependence among various brain regions. Through its wide use in studying brain connectivity, the low temporal resolution of the fMRI represented by the limited number of samples per second, in addition to its dependence on brain slow hemodynamic changes, makes it of limited capability in studying the fast underlying neural processes during information exchange between brain regions. Materials and Methods: In this article, the high temporal resolution of the electroencephalography (EEG) is utilized to estimate the effective connectivity within the default mode network (DMN). The EEG data are collected from 20 subjects with alcoholism and 25 healthy subjects (controls), and used to obtain the effective connectivity diagram of the DMN using the Partial Directed Coherence algorithm. Results: The resulting effective connectivity diagram within the DMN shows the unidirectional causal effect of each region on the other. The variations in the causal effects within the DMN between controls and alcoholics show clear correlation with the symptoms that are usually associated with alcoholism, such as cognitive and memory impairments, executive control, and attention deficiency. The correlation between the exchanged causal effects within the DMN and symptoms related to alcoholism is discussed and properly analyzed. Conclusion: The establishment of the causal differences between control and alcoholic subjects within the DMN regions provides valuable insight into the mechanism by which alcohol modulates our cognitive and executive functions and creates better possibility for effective treatment of alcohol use disorder.
  4. A novel method for efficient estimation of brain effective connectivity in EEG
    Khan DM, Yahya N, Kamel N, Faye I
    Comput Methods Programs Biomed, 2023 Jan;228:107242.
    PMID: 36423484 DOI: 10.1016/j.cmpb.2022.107242
    BACKGROUND AND OBJECTIVE: Brain connectivity plays a pivotal role in understanding the brain's information processing functions by providing various details including magnitude, direction, and temporal dynamics of inter-neuron connections. While the connectivity may be classified as structural, functional and causal, a complete in-vivo directional analysis is guaranteed by the latter and is referred to as Effective Connectivity (EC). Two most widely used EC techniques are Directed Transfer Function (DTF) and Partial Directed Coherence (PDC) which are based on multivariate autoregressive models. The drawbacks of these techniques include poor frequency resolution and the requirement for experimental approach to determine signal normalization and thresholding techniques in identifying significant connectivities between multivariate sources.

    METHODS: In this study, the drawbacks of DTF and PDC are addressed by proposing a novel technique, termed as Efficient Effective Connectivity (EEC), for the estimation of EC between multivariate sources using AR spectral estimation and Granger causality principle. In EEC, a linear predictive filter with AR coefficients obtained via multivariate EEG is used for signal prediction. This leads to the estimation of full-length signals which are then transformed into frequency domain by using Burg spectral estimation method. Furthermore, the newly proposed normalization method addressed the effect on each source in EEC using the sum of maximum connectivity values over the entire frequency range. Lastly, the proposed dynamic thresholding works by subtracting the first moment of causal effects of all the sources on one source from individual connections present for that source.

    RESULTS: The proposed method is evaluated using synthetic and real resting-state EEG of 46 healthy controls. A 3D-Convolutional Neural Network is trained and tested using the PDC and EEC samples. The result indicates that compared to PDC, EEC improves the EEG eye-state classification accuracy, sensitivity and specificity by 5.57%, 3.15% and 8.74%, respectively.

    CONCLUSION: Correct identification of all connections in synthetic data and improved resting-state classification performance using EEC proved that EEC gives better estimation of directed causality and indicates that it can be used for reliable understanding of brain mechanisms. Conclusively, the proposed technique may open up new research dimensions for clinical diagnosis of mental disorders.

  5. Effective Connectivity for Decoding Electroencephalographic Motor Imagery Using a Probabilistic Neural Network
    Awais MA, Yusoff MZ, Khan DM, Yahya N, Kamel N, Ebrahim M
    Sensors (Basel), 2021 Sep 30;21(19).
    PMID: 34640888 DOI: 10.3390/s21196570
    Motor imagery (MI)-based brain-computer interfaces have gained much attention in the last few years. They provide the ability to control external devices, such as prosthetic arms and wheelchairs, by using brain activities. Several researchers have reported the inter-communication of multiple brain regions during motor tasks, thus making it difficult to isolate one or two brain regions in which motor activities take place. Therefore, a deeper understanding of the brain's neural patterns is important for BCI in order to provide more useful and insightful features. Thus, brain connectivity provides a promising approach to solving the stated shortcomings by considering inter-channel/region relationships during motor imagination. This study used effective connectivity in the brain in terms of the partial directed coherence (PDC) and directed transfer function (DTF) as intensively unconventional feature sets for motor imagery (MI) classification. MANOVA-based analysis was performed to identify statistically significant connectivity pairs. Furthermore, the study sought to predict MI patterns by using four classification algorithms-an SVM, KNN, decision tree, and probabilistic neural network. The study provides a comparative analysis of all of the classification methods using two-class MI data extracted from the PhysioNet EEG database. The proposed techniques based on a probabilistic neural network (PNN) as a classifier and PDC as a feature set outperformed the other classification and feature extraction techniques with a superior classification accuracy and a lower error rate. The research findings indicate that when the PDC was used as a feature set, the PNN attained the greatest overall average accuracy of 98.65%, whereas the same classifier was used to attain the greatest accuracy of 82.81% with the DTF. This study validates the activation of multiple brain regions during a motor task by achieving better classification outcomes through brain connectivity as compared to conventional features. Since the PDC outperformed the DTF as a feature set with its superior classification accuracy and low error rate, it has great potential for application in MI-based brain-computer interfaces.
  6. Fulltext Scavenging of caffeine from aqueous medium through optimized H3PO4-activated Acacia mangium wood activated carbon: Statistical data of optimization
    Danish M, Birnbach J, Mohamad Ibrahim MN, Hashim R
    Data Brief, 2020 Feb;28:105045.
    PMID: 31921950 DOI: 10.1016/j.dib.2019.105045
    The optimization data presented here are part of the study planned to remove the caffeine from aqueous solution through the large surface area optimized H3PO4-activated Acacia mangium wood activated carbon (OAMW-AC). The maximum adsorption capacity of the OAMW-AC for caffeine adsorption was achieved (30.3 mg/g) through optimized independent variables such as, OAMW-AC dosage (3.0 g/L), initial caffeine concentration (100 mg/L), contact time (60 min), and solution pH (7.7). The adsorption capacity of OAMW-AC was optimized with the help of rotatable central composite design of response surface methodology. Under the stated optimized conditions for maximum adsorption capacity, the removal efficiency was calculated to be 93%. The statistical significance of the data set was tested through the analysis of variance (ANOVA) study. Data confirmed the statistical model for caffeine adsorption was significant. The regression coefficient (R2) of curve fitting through the quadratic model was found to be 0.9832, and the adjusted regression coefficient was observed to be 0.9675.
  7. Aluminum dispersed bamboo activated carbon production for effective removal of Ciprofloxacin hydrochloride antibiotics: Optimization and mechanism study
    Guellati A, Maachi R, Chaabane T, Darchen A, Danish M
    J Environ Manage, 2022 Jan 01;301:113765.
    PMID: 34592665 DOI: 10.1016/j.jenvman.2021.113765
    The central composite rotatable design (CCD) of response surface methodology (RSM) was used to optimize aluminum dispersed bamboo activated carbon preparation. The independent variables selected for optimization are activating agent (AlCl3) concentration (mol/L), activation temperature (°C), and activation time (min.). The independent variable's response change was observed through the percentage adsorption efficiency of Ciprofloxacin hydrochloride (CIP) antibiotics. The maximum CIP adsorption efficiency was found to be 93.6 ± 0.36% (13.36 mg/g) for the adsorbent prepared at AlCl3 concentration 2.0 mol/L, activation temperature 900 °C, and activation time 120 min. The adsorption efficiency was recorded at the natural pH (7.9) of the adsorbent (3 g/L)-adsorbate (50 mL solution of 50 ppm) mixture. The Al-dispersed bamboo activated carbon was characterized for its surface morphology, surface elemental compositions, molecular crystallinity, surface area, pore morphology, and surface functional groups. The mechanism of adsorbent surface formation and CIP adsorption sites were explored. The characterization data and mechanism study will help in deciding possible future applications in other fields of study.
  8. High surface area mesoporous activated carbon-alginate beads for efficient removal of methylene blue
    Nasrullah A, Bhat AH, Naeem A, Isa MH, Danish M
    Int J Biol Macromol, 2018 Feb;107(Pt B):1792-1799.
    PMID: 29032214 DOI: 10.1016/j.ijbiomac.2017.10.045
    High surface area mesoporous activated carbon-alginate (AC-alginate) beads were successfully synthesized by entrapping activated carbon powder derived from Mangosteen fruit peel into calcium-alginate beads for methylene blue (MB) removal from aqueous solution. The structure and surface characteristics of AC-alginate beads were analyzed using Fourier transform infra-red (FTIR) spectroscopy, scanning electron microscopy (SEM) and surface area analysis (SBET), while thermal properties were tested using thermogravimetric analysis (TGA). The effect of AC-alginate dose, pH of solution, contact time, initial concentration of MB solution and temperature on MB removal was elucidated. The results showed that the maximum adsorption capacity of 230mg/g was achieved for 100mg/L of MB solution at pH 9.5 and temperature 25°C. Furthermore, the adsorption of MB on AC-alginate beads followed well pseudo-second order equation and equilibrium adsorption data were better fitted by the Freundlich isotherm model. The findings reveal the feasibility of AC-alginate beads composite to be used as a potential and low cost adsorbent for removal of cationic dyes.
  9. Bioengineered silver nanoparticles capped with bovine serum albumin and its anticancer and apoptotic activity against breast, bone and intestinal colon cancer cell lines
    Majeed S, Aripin FHB, Shoeb NSB, Danish M, Ibrahim MNM, Hashim R
    Mater Sci Eng C Mater Biol Appl, 2019 Sep;102:254-263.
    PMID: 31146998 DOI: 10.1016/j.msec.2019.04.041
    The aim of the current study was to biosynthesize the silver nanoparticles (AgNPs) from the bacterial strain of Bacillus cereus (ATCC 14579) extracellularly. When bacterial extract was challenged with 1 mM silver nitrate (AgNO3) the color of the extract changed into brown confirms the formation of nanoparticles. These nanoparticles were capped with bovine serum albumin (BSA). UV- visible spectroscopy showed the absorption peak at 420 nm indicates the formation of AgNPs. Fourier Infra -red (FTIR) attenuated total reflection (ATR) spectroscopy showed amide and amine group associated with AgNPs that stabilizes the nanoparticles. Energy dispersive x-ray spectroscopy (EDX) showed a strong peak of silver confirms the presence of silver. Thermo gravimetric analysis (TGA) analysis was used to determine the protein degradation showed less protein degradation at higher temperature confirms the stability of nanoparticles. Transmission electron microscopy (TEM) showed the AgNPs are well dispersed and spherical, and 5.37 nm to 17.19 whereas albumin coated nanoparticles are size ranges from 11.26 nm to 23.85 nm. The anticancer effect of capped AgNPs (cAgNPs) showed the IC50 value against breast cancer MCF-7 at 80 μg/mL, intestinal colon cancer HCT- 116 60 μg/mL, and bone cancer osteosarcoma MG-63 cell line80 μg/mL while against normal fibroblast cells 3T3 cells showed the IC50 value at 140 μg/mL. Lactate dehydrogenase assay (LDH) showed higher toxicity on MCF-7, HCT-116, and MG-63 cells. The apoptotic study clearly showed the blebbing of membrane, chromatin condensation due to the production of reactive oxygen species (ROS) by ethidium bromide and acridine orange dual staining method. The DNA analysis showed the complete fragmentation of the DNA of treated cells when compared with control cells.
  10. Fulltext Investigations on Surface Roughness and Tool Wear Characteristics in Micro-Turning of Ti-6Al-4V Alloy
    Aslantas K, Danish M, Hasçelik A, Mia M, Gupta M, Ginta T, et al.
    Materials (Basel), 2020 Jul 06;13(13).
    PMID: 32640567 DOI: 10.3390/ma13132998
    Micro-turning is a micro-mechanical cutting method used to produce small diameter cylindrical parts. Since the diameter of the part is usually small, it may be a little difficult to improve the surface quality by a second operation, such as grinding. Therefore, it is important to obtain the good surface finish in micro turning process using the ideal cutting parameters. Here, the multi-objective optimization of micro-turning process parameters such as cutting speed, feed rate and depth of cut were performed by response surface method (RSM). Two important machining indices, such as surface roughness and material removal rate, were simultaneously optimized in the micro-turning of a Ti6Al4V alloy. Further, the scanning electron microscope (SEM) analysis was done on the cutting tools. The overall results depict that the feed rate is the prominent factor that significantly affects the responses in micro-turning operation. Moreover, the SEM results confirmed that abrasion and crater wear mechanism were observed during the micro-turning of a Ti6Al4V alloy.
  11. Fulltext Conversion of flaxseed oil into biodiesel using KOH catalyst: Optimization and characterization dataset
    Danish M, Kale P, Ahmad T, Ayoub M, Geremew B, Adeloju S
    Data Brief, 2020 Apr;29:105225.
    PMID: 32154335 DOI: 10.1016/j.dib.2020.105225
    The dataset presented here are part of the data planned to produce biodiesel from flaxseed. Biodiesel production from flaxseed oil through transesterification process using KOH as catalyst, and the operating parameters were optimized with the help of face-centered central composite design (FCCD) of response surface methodology (RSM). The operating independent variables selected such as, methanol oil ratio (4:1 to 6:1), catalyst (KOH) weight (0.40-1.0%), temperature (35 °C-65 °C), and reaction time (30 min-60 min) were optimized against biodiesel yield as response. The maximum yield (98.6%) of biodiesel from flaxseed can achieved at optimum methanol oil ratio (5.9:1), catalyst (KOH) weight (0.51%), reaction temperature (59.2 °C), and reaction time (33 min). The statistical significance of the data set was tested through the analysis of variance (ANOVA). These data were the part of the results reported in "Optimization of process variables for biodiesel production by transesterification of flaxseed oil and produced biodiesel characterizations" Renewable Energy [1].
  12. Application of optimized large surface area date stone (Phoenix dactylifera ) activated carbon for rhodamin B removal from aqueous solution: Box-Behnken design approach
    Danish M, Khanday WA, Hashim R, Sulaiman NS, Akhtar MN, Nizami M
    Ecotoxicol Environ Saf, 2017 May;139:280-290.
    PMID: 28167440 DOI: 10.1016/j.ecoenv.2017.02.001
    Box-Behnken model of response surface methodology was used to study the effect of adsorption process parameters for Rhodamine B (RhB) removal from aqueous solution through optimized large surface area date stone activated carbon. The set experiments with three input parameters such as time (10-600min), adsorbent dosage (0.5-10g/L) and temperature (25-50°C) were considered for statistical significance. The adequate relation was found between the input variables and response (removal percentage of RhB) and Fisher values (F- values) along with P-values suggesting the significance of various term coefficients. At an optimum adsorbent dose of 0.53g/L, time 593min and temperature 46.20°C, the adsorption capacity of 210mg/g was attained with maximum desirability. The negative values of Gibb(')s free energy (ΔG) predicted spontaneity and feasibility of adsorption; whereas, positive Enthalpy change (ΔH) confirmed endothermic adsorption of RhB onto optimized large surface area date stone activated carbons (OLSADS-AC). The adsorption data were found to be the best fit on the Langmuir model supporting monolayer type of adsorption of RhB with maximum monolayer layer adsorption capacity of 196.08mg/g.
  13. The use of date palm as a potential adsorbent for wastewater treatment: a review
    Ahmad T, Danish M, Rafatullah M, Ghazali A, Sulaiman O, Hashim R, et al.
    Environ Sci Pollut Res Int, 2012 Jun;19(5):1464-84.
    PMID: 22207239 DOI: 10.1007/s11356-011-0709-8
    BACKGROUND: In tropical countries, the palm tree is one of the most abundant and important trees. Date palm is a principal fruit grown in many regions of the world. It is abundant, locally available and effective material that could be used as an adsorbent for the removal of different pollutants from aqueous solution.

    REVIEW: This article presents a review on the role of date palm as adsorbents in the removal of unwanted materials such as acid and basic dyes, heavy metals, and phenolic compounds. Many studies on adsorption properties of various low cost adsorbent, such as agricultural waste and activated carbons based on agricultural waste have been reported in recent years.

    CONCLUSION: Studies have shown that date palm-based adsorbents are the most promising adsorbents for removing unwanted materials. No previous review is available where researchers can get an overview of the adsorption capacities of date palm-based adsorbent used for the adsorption of different pollutants. This review provides the recent literature demonstrating the usefulness of date palm biomass-based adsorbents in the adsorption of various pollutants.

  14. A review of pre- and post-surface-modified neem (Azadirachta indica) biomass adsorbent: Surface functionalization mechanism and application
    Karim AR, Danish M, Alam MG, Majeed S, Alanazi AM
    Chemosphere, 2024 Mar;351:141180.
    PMID: 38218237 DOI: 10.1016/j.chemosphere.2024.141180
    In contemporary wastewater treatment industry, advanced oxidation techniques, membrane filtration, ion exchange, and reverse osmosis are used to treat chemically loaded wastewater. All these methods required highly toxic oxidizing chemicals, high capital investment in membrane/filter materials, and the installation of sophisticated equipment. Wastewater treatment through an adsorption process using biomass-based adsorbent is economical, user-friendly, and sustainable. Neem tree waste has been explored as an adsorbent for wastewater treatment. The chemical components in the neem biomass include carbohydrates, fat, fiber, cellulose, hemicellulose, and lignin, which support the functionalization of neem biomass. Moreover, adsorbent preparation from renewable resources is not only cost-effective and environmentally friendly but also helps in waste management for sustainable growth. Contemporary researchers explored the pre- and post-surface-modified neem biomass adsorbents in scavenging the pollutants from contaminated water. This review extensively explores the activation process of neem biomass, physical and chemical methods of surface modification mechanism, and the factors affecting surface modification. The pollutant removal through pre and post-surface-modified neem biomass adsorbents was also summarized. Furthermore, it also provides a comprehensive summary of the factors that affect the adsorption performance of the neem biomass-derived adsorbents against dyes, metal ions, and other emerging pollutants. Understanding the surface-modification mechanisms and the adsorption efficiency factor of adsorbents will help in harnessing their potential for more efficiently combatting environmental pollution and making strides toward a greener and more sustainable future.
  15. Fulltext Analysis using image segmentation for the elemental composition of activated carbon
    Danish M, Akhtar MN, Hashim R, Saleh JM, Bakar EA
    MethodsX, 2020;7:100983.
    PMID: 32742942 DOI: 10.1016/j.mex.2020.100983
    This article encompasses the method related to image segmentation of the Field Emission Scanning Electron Microscope (FESEM) images of Acacia Mangium Wood derived Activated Carbons under different conditions. Image segmentation using Hue-Saturation-Value (HSV) thresholding method was adapted to identify the different pattern composition in the grayscale images by varying the intensity Value (V) and keeping Hue (H) and Saturation (S) to zero, and each pattern was considered as one type of element that constituted the Activated Carbon. The algorithm was developed to compute the percentage of each pattern using non-zero pixels, and on the basis of different patterns, different elements having certain percentage of composition were recorded. Later, these results were compared with the Energy Dispersive X-ray Spectroscopy (EDS) to cross check the difference in percentage of each element present at the surface of the Activated Carbon. Part of this result is published in the article [1], "Comparison of surface properties of wood biomass Activated Carbons and their application against rhodamine B and methylene blue dye" Surfaces and Interfaces vol. 11 (2018) pp1-13.•The methods involved will be useful for characterization of Activated Carbon materials.•Image segmentation using HSV thresholding will inspire other researchers to apply similar concept on other materials.•Different patterns obtained for FESEM images using HSV thresholding was able to determine the presence of multiple elements present in the prepared Activated Carbon samples.
  16. Fulltext Investigation of Coatings, Corrosion and Wear Characteristics of Machined Biomaterials through Hydroxyapatite Mixed-EDM Process: A Review
    Al-Amin M, Abdul-Rani AM, Danish M, Rubaiee S, Mahfouz AB, Thompson HM, et al.
    Materials (Basel), 2021 Jun 28;14(13).
    PMID: 34203154 DOI: 10.3390/ma14133597
    Together, 316L steel, magnesium-alloy, Ni-Ti, titanium-alloy, and cobalt-alloy are commonly employed biomaterials for biomedical applications due to their excellent mechanical characteristics and resistance to corrosion, even though at times they can be incompatible with the body. This is attributed to their poor biofunction, whereby they tend to release contaminants from their attenuated surfaces. Coating of the surface is therefore required to mitigate the release of contaminants. The coating of biomaterials can be achieved through either physical or chemical deposition techniques. However, a newly developed manufacturing process, known as powder mixed-electro discharge machining (PM-EDM), is enabling these biomaterials to be concurrently machined and coated. Thermoelectrical processes allow the migration and removal of the materials from the machined surface caused by melting and chemical reactions during the machining. Hydroxyapatite powder (HAp), yielding Ca, P, and O, is widely used to form biocompatible coatings. The HAp added-EDM process has been reported to significantly improve the coating properties, corrosion, and wear resistance, and biofunctions of biomaterials. This article extensively explores the current development of bio-coatings and the wear and corrosion characteristics of biomaterials through the HAp mixed-EDM process, including the importance of these for biomaterial performance. This review presents a comparative analysis of machined surface properties using the existing deposition methods and the EDM technique employing HAp. The dominance of the process factors over the performance is discussed thoroughly. This study also discusses challenges and areas for future research.
  17. Evaluating ionic liquids for its potential as eco-friendly solvents for naproxen removal from water sources using COSMO-RS: Computational and experimental validation
    Warsi Khan H, Kaif Khan M, Moniruzzaman M, Al Mesfer MK, Danish M, Irshad K, et al.
    Environ Res, 2023 Aug 15;231(Pt 1):116058.
    PMID: 37178749 DOI: 10.1016/j.envres.2023.116058
    An emerging contaminant of concern in aqueous streams is naproxen. Due to its poor solubility, non-biodegradability, and pharmaceutically active nature, the separation is challenging. Conventional solvents employed for naproxen are toxic and harmful. Ionic liquids (ILs) have attracted great attention as greener solubilizing and separating agent for various pharmaceuticals. ILs have found extensive usage as solvents in nanotechnological processes involving enzymatic reactions and whole cells. The employment of ILs can enhance the effectiveness and productivity of such bioprocesses. To avoid cumbersome experimental screening, in this study, conductor like screening model for real solvents (COSMO-RS) was used to screen ILs. Thirty anions and eight cations from various families were chosen. Activity coefficient at infinite dilution, capacity, selectivity, performance index, molecular interactions using σ-profiles and interaction energies were used to make predictions about solubility. According to the findings, quaternary ammonium cations, highly electronegative, and food-grade anions will form excellent ionic liquid combinations for solubilizing naproxen and hence will be better separating agents. This research will contribute easy designing of ionic liquid-based separation technologies for naproxen. In different separation technologies, ionic liquids can be employed as extractants, carriers, adsorbents, and absorbents.
  18. Multi-objective optimization of thermophysical properties of multiwalled carbon nanotubes based nanofluids
    Maqsood K, Ali A, Ilyas SU, Garg S, Danish M, Abdulrahman A, et al.
    Chemosphere, 2022 Jan;286(Pt 2):131690.
    PMID: 34352553 DOI: 10.1016/j.chemosphere.2021.131690
    The experimental determination of thermophysical properties of nanofluid (NF) is time-consuming and costly, leading to the use of soft computing methods such as response surface methodology (RSM) and artificial neural network (ANN) to estimate these properties. The present study involves modelling and optimization of thermal conductivity and viscosity of NF, which comprises multi-walled carbon nanotubes (MWCNTs) and thermal oil. The modelling is performed to predict the thermal conductivity and viscosity of NF by using Response Surface Methodology (RSM) and Artificial Neural Network (ANN). Both models were tested and validated, which showed promising results. In addition, a detailed optimization study was conducted to investigate the optimum thermal conductivity and viscosity by varying temperature and NF weight per cent. Four case studies were explored using different objective functions based on NF application in various industries. The first case study aimed to maximize thermal conductivity (0.15985 W/m oC) while minimizing viscosity (0.03501 Pa s) obtained at 57.86 °C and 0.85 NF wt%. The goal of the second case study was to minimize thermal conductivity (0.13949 W/m °C) and viscosity (0.02526 Pa s) obtained at 55.88 °C and 0.15 NF wt%. The third case study targeted maximizing thermal conductivity (0.15797 W/m °C) and viscosity (0.07611 Pa s), and the optimum temperature and NF wt% were 30.64 °C and 0.0.85,' respectively. The last case study explored the minimum thermal conductivity (0.13735) and maximum viscosity (0.05263 Pa s) obtained at 30.64 °C and 0.15 NF wt%.
Related Terms
    Try searching for something
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links